Determining projection constants of univariate polynomial spaces

JOURNAL OF APPROXIMATION THEORY

卷:235

Article

Foucart, Simon¹  Lasserre, Jean B.^2,3 

[1] Texas A&M Univ, College Stn, TX 77843 USA

[2] Univ Toulouse, CNRS, LAAS, Toulouse, France

[3] Univ Toulouse, Inst Math, Toulouse, France

关键词: Minimal projection;    Projection constant;    Linear programming;    Semidefinite programming;    Method of moments;   

DOI  :  10.1016/j.jat.2018.06.002

来源: Elsevier

【 摘 要 】

The long-standing problem of minimal projections is addressed from a computational point of view. Techniques to determine bounds on the projection constants of univariate polynomial spaces are presented. The upper bound, produced by a linear program, and the lower bound, produced by a semidefinite program exploiting the method of moments, are often close enough to deduce the projection constant with reasonable accuracy. The implementation of these programs makes it possible to find the projection constant of several three-dimensional spaces with five digits of accuracy, as well as the projection constants of the spaces of cubic, quartic, and quintic polynomials with four digits of accuracy. Beliefs about uniqueness and shape preservation of minimal projections are contested along the way. (C) 2018 Elsevier Inc. All rights reserved.

【 授权许可】

Free